Tech Reports

ULCS-08-018

Formal Models of Reproduction: from Computer Viruses to Artificial Life (PhD Thesis)

Matthew Paul Webster

Abstract

In this thesis we describe novel approaches to the formal description
of systems which reproduce, and show that the resulting models have
explanatory power and practical applications, particularly in the domain
of computer virology. We start by generating a formal description of
computer viruses based on formal methods and notations developed for
software engineering. We then prove that our model can be used to detect
metamorphic computer viruses, which are designed specifically to avoid
well-established signature-based detection methods. Next, we move away
from the specific case of reproducing programs, and consider formal
models of reproducing things in general. We show that we can develop
formal models of the ecology of a reproducer, based on a formalisation
of Gibson’s theory of affordances. These models can be classified and
refined formally, and we show how refinements allow us to relate models
in interesting ways. We then prove that there are restrictions and rules
concerning classification based on assistance and triviality, and
explore the philosophical implications of our theoretical results. We
then apply our formal affordance-based reproduction models to the
detection of computer viruses, showing that the different
classifications of a computer virus reproduction model correspond to
differences between anti-virus behaviour monitoring software. Therefore,
we end the main part of the thesis in the same mode in which we started,
tackling the real-life problem of computer virus detection. In the
conclusion we lay out the novel contributions of this thesis, and
explore directions for future research."

For each technical report listed here, copyright and all intellectual property rights remain with the respective authors. Copyright is effective from the year of publication in each case. By downloading a file from this page, you agree to use it only for purposes of research and scholarship. Any other use of this material or storage of it in any medium or its sale or distribution in any form is expressly forbidden without prior written permission from the authors concerned.